Speech is perhaps the oldest form of human communication and many scientists now believe that the ability to communicate through vocalization is inherently provided in the biology of the human brain. Thus, it has been a long-sought goal to allow users to communicate with computers using a Natural User Interface (NUI), such as speech. In fact, recently great strides have been made in obtaining this goal. For example, some computers now include speech recognition applications that allow a user to vocally input both commands for operating the computer and dictation to be converted into text. These applications typically operate by periodically recording sound samples taken through a microphone, analyzing the samples to recognize the phonemes being spoken by the user and identifying the words made up by the spoken phonemes.
While speech recognition is becoming more commonplace, there are still some disadvantages to using conventional speech recognition applications that tend to frustrate the experienced user and alienate the novice user. One such disadvantage involves the interaction between the speaker and the computer. For example, with human interaction, people tend to control their speech based upon the reaction that they perceive in a listener. As such, during a conversation, a listener may provide feedback by nodding or making vocal responses, such as “yes” or “uh-huh”, to indicate that he or she understands what is being said to them. Additionally, if the listener does not understand what is being said to them, the listener may take on a quizzical expression, lean forward, or give other vocal or non-vocal cues. In response to this feedback, the speaker will typically change the way he or she is speaking and in some cases, the speaker may speak more slowly, more loudly, pause more frequently, or even repeat a statement, usually without the listener even realizing that the speaker is changing the way they are interacting with the listener. Thus, feedback during a conversation is a very important element that informs the speaker as to whether or not they are being understood. Unfortunately however, conventional voice recognition applications are not yet able to provide this type of “Natural User Interface (NUI)” feedback response to speech inputs/commands facilitated by a man-machine interface.
Currently, voice recognition applications have achieved an accuracy rate of 90% to 98%. This means that when a user dictates into a document using a typical voice recognition application their speech will be accurately recognized by the voice recognition application approximately 90% to 98% of the time. Thus, out of every one hundred (100) letters recorded by the voice recognition application, approximately two (2) to ten (10) letters will have to be corrected. Two common ways to address this problem and correct misrecognized letter or words involves the repeating, or re-speaking, of a letter or word or the requesting of a speech alternative. However, these two approaches do not work every time the user performs a correction and is thus particularly disadvantageous to a certain class of user that must use speech when performing corrections, e.g. those users who are physically unable to use a keyboard.
Another approach to addressing this problem and correcting a misrecognized letter or word that is displayed on a display screen, involves deleting the entire word and respelling the word from the beginning For example, to change the word “intent” to “indent”, the user would have to say “delete intent” and then re-spell the desired word by saying “i”, “n”, “d”, “e”, “n”, “t”. Still another approach to addressing this problem and correcting the misrecognized word that is displayed on a display screen involves controlling the keyboard by voice to change the letters which are wrong. In this case, the user must delete all of the letters in a word up to the letter which needs to be changed. Then they respell the rest. For example, to change the word “intent” to “indent”, the user would say “backspace backspace backspace backspace”, and then re-spell the desired word by saying “d”, “e”, “n”, “t”.
Unfortunately however, these approaches have several disadvantages associated with them. First, a large number of commands are required to change one letter. Second, these approaches rely on the respelling of a large number of letters and, as the current state of the art Speech Recognition accuracy is only nine (9) letters in ten (10) are correct, this means that after having to correct just two or three words by resorting to re-spelling, the user is statistically likely to get an error. This means that the user has to pause after each letter to ensure that it is correct (which adds time) or the user has to endure the fact that they will likely have to say “backspace backspace . . . ” then re-spell the word again on multiple occasions. Third, because speech recognition mistakes are often only a couple of letters different from the word that the user intended, very often the word whose spelling the user is manipulating is very close to the word the user intended. Not only do these disadvantages tend to create frustration in frequent users, but they also tend to be discouraging to novice users as well, possibly resulting in the user refusing to continue employing the voice recognition application.